The aim of this study is to develop a machine learning model using Python's FastAPI library and then to perform model deployment processes in order to make these models usable in real world applications and to make them accessible to users (businesses) or other systems. After the deployment process, the model was converted into a Docker image in order to facilitate the development, testing and production processes by ensuring that the application works in an independent, portable and consistent manner. In addition, since Docker images can be used in cloud environments to make deployment processes more effective, this image was used in MLOps End-To-End repostory to be shared with servers in Google Cloud environment.
- You can access the repository containing MLOps CI/CD processes from this link: